June 6, 2024, 4:42 a.m. | Simon Zhang, Soham Mukherjee, Tamal K. Dey

cs.LG updates on arXiv.org arxiv.org

arXiv:2406.02732v1 Announce Type: new
Abstract: Extended persistence is a technique from topological data analysis to obtain global multiscale topological information from a graph. This includes information about connected components and cycles that are captured by the so-called persistence barcodes. We introduce extended persistence into a supervised learning framework for graph classification. Global topological information, in the form of a barcode with four different types of bars and their explicit cycle representatives, is combined into the model by the readout function …

abstract analysis arxiv classification components cs.ds cs.lg data data analysis framework global graph information persistence supervised learning type

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